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      Gene expression profiling of chromophobe renal cell carcinomas and renal oncocytomas by Affymetrix GeneChip using pooled and individual tumours

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          Abstract

          Due to overlapping morphology, malignant chromophobe renal cell carcinomas (RCC) and benign renal oncocytomas (RO) may pose a diagnostic problem. In the present study, we have applied different algorithms to evaluate the data sets obtained by hybridisation of pooled and also individual samples of renal cell tumours (RCT) onto two different gene expression platforms. The two approaches revealed high similarities in the gene expression profiles of chromophobe RCCs and ROs but also some differences. After identifying the differentially expressed genes by statistic analyses, the candidate genes were further selected by a real time and normal RT-PCR and their products were analysed by immunohistochemistry. We have identified CD82 and S100A1 as valuable markers for chromophobe RCC as well as AQP6 for ROs. However, these genes are expressed at the protein level in other types of RCTs as well albeit at a low frequency and low intensity. As none of the selected genes marks exclusively one type of RCTs, for the differential diagnosis of chromophobe RCCs and ROs, a set of markers such as CD82, S100A1 and AQP6 as well as some others would be an option in routine histological laboratories.

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          Gene signatures of progression and metastasis in renal cell cancer.

          To address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC). Transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. Gene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumor was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC. Unlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC.
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            High-resolution DNA copy number and gene expression analyses distinguish chromophobe renal cell carcinomas and renal oncocytomas

            Background The diagnosis of benign renal oncocytomas (RO) and chromophobe renal cell carcinomas (RCC) based on their morphology remains uncertain in several cases. Methods We have applied Affymetrix GeneChip Mapping 250 K NspI high-density oligoarrays to identify small genomic alterations, which may occur beyond the specific losses of entire chromosomes, and also Affymetrix GeneChip HG-U133 Plus2.0 oligoarrays for gene expression profiling. Results By analysing of DNA extracted from 30 chRCCs and 42 ROs, we have confirmed the high specificity of monosomies of chromosomes 1, 2, 6, 10, 13, 17 and 21 in 70–93% of the chRCCs, while ROs displayed loss of chromosome 1 and 14 in 24% and 5% of the cases, respectively. We demonstrated that chromosomal gene expression biases might correlate with chromosomal abnormalities found in chromophobe RCCs and ROs. The vast majority genes downregulated in chromophobe RCC were mapped to chromosomes 2, 6, 10, 13 and 17. However, most of the genes overexpressed in chromophobe RCCs were located to chromosomes without any copy number changes indicating a transcriptional regulation as a main event. Conclusion The SNP-array analysis failed to detect recurrent small deletions, which may mark loci of genes involved in the tumor development. However, we have identified loss of chromosome 2, 10, 13, 17 and 21 as discriminating alteration between chromophobe RCCs and ROs. Therefore, detection of these chromosomal changes can be used for the accurate diagnosis in routine histology.
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              Gene expression patterns in renal cell carcinoma assessed by complementary DNA microarray.

              Renal cell carcinoma comprises several histological types with different clinical behavior. Accurate pathological characterization is important in the clinical management of these tumors. We describe gene expression profiles in 41 renal tumors determined by using DNA microarrays containing 22,648 unique cDNAs representing 17,083 different UniGene Clusters, including 7230 characterized human genes. Differences in the patterns of gene expression among the different tumor types were readily apparent; hierarchical cluster analysis of the tumor samples segregated histologically distinct tumor types solely based on their gene expression patterns. Conventional renal cell carcinomas with clear cells showed a highly distinctive pattern of gene expression. Papillary carcinomas formed a tightly clustered group, as did tumors arising from the distal nephron and the normal kidney samples. Surprisingly, conventional renal cell carcinomas with granular cytoplasm were heterogeneous, and did not resemble any of the conventional carcinomas with clear cytoplasm in their pattern of gene expression. Characterization of renal cell carcinomas based on gene expression patterns provides a revised classification of these tumors and has the potential to supply significant biological and clinical insights.
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                Author and article information

                Journal
                Int J Biol Sci
                ijbs
                International Journal of Biological Sciences
                Ivyspring International Publisher (Sydney )
                1449-2288
                2009
                29 July 2009
                : 5
                : 6
                : 517-527
                Affiliations
                Laboratory of Molecular Oncology, Medical Faculty, Ruprecht-Karls University, Heidelberg, Germany
                Author notes
                ✉ Correspondence to: G Kovacs, Laboratory of Molecular Oncology, Medical Faculty, Ruprecht-Karls-University, Im Neuenheimer Feld 325, D-69120 Heidelberg, Germany. Phone: 49-6221-566519, Fax: 49-6221-564634, E-mail: gyula.kovacs@ 123456urz.uni-heidelberg.de

                * Present address: Department of Forensic Molecular Biology, Erasmus University Medical Centre Rotterdam, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands

                Conflict of interests: The authors declare that no conflict of interest exists.

                Article
                ijbsv05p0517
                10.7150/ijbs.5.517
                2726578
                19680475
                87ccbeb3-9058-400e-ae45-60e96c70aacb
                © Ivyspring International Publisher. This is an open-access article distributed under the terms of the Creative Commons License (http://creativecommons.org/licenses/by-nc-nd/3.0/). Reproduction is permitted for personal, noncommercial use, provided that the article is in whole, unmodified, and properly cited.
                History
                : 10 June 2009
                : 25 July 2009
                Categories
                Research Paper

                Life sciences
                gene expression profile,ihc,chromophobe renal cell carcinoma,diagnosis.,real-time pcr

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